Strong hands-on experience with Databricks and Apache Spark.
Proficiency in Python and Scala for data processing and application development.
Hands-on experience with Hadoop and big data technologies.
Experience with Control-M for batch scheduling and workflow orchestration.
Strong understanding of ETL/ELT processes and distributed data processing.
Excellent analytical, problem-solving, and collaboration skills.
Responsibilities
Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala.
Develop and optimize ETL/ELT processes for data ingestion and transformation.
Process and manage large volumes of structured and unstructured data using Hadoop.
Troubleshoot and optimize Spark applications for performance and reliability.
Schedule, monitor, and manage batch jobs using Control-M.
Resolve data pipeline issues and ensure timely completion of workloads.
Implement data validation and quality checks for accuracy and consistency.
Benefits
Drive High-Impact Business Transformation through enterprise-wide AI adoption and data modernization.
Collaborate with exceptional talent across geographies to deliver transformative solutions.
Comprehensive benefits including Medical, Dental, Vision, and Retirement Accounts.
Continuous learning opportunities in emerging technologies and AI upskilling.
Discretionary time-off to promote work-life balance.
Full Job Description
What you will be doing
We are seeking a Senior Data Engineer to join our advanced analytics and AI team supporting some of our large enterprise clients. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines, processing large datasets, and managing scheduled data workflows to support enterprise data engineering initiatives.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, Python, and Scala.
Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources.
Work with Hadoop and its ecosystem to process and manage large volumes of structured and unstructured data.
Develop, troubleshoot, and optimize Spark applications to improve performance, scalability, and reliability.
Use Control-M to schedule, monitor, and manage batch jobs, workflow dependencies, and data processing pipelines.
Troubleshoot job failures, resolve data pipeline issues, and ensure timely completion of scheduled workloads.
Implement data validation, error handling, and quality checks to ensure data accuracy and consistency.
Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions.
Follow coding standards, testing practices, version control, and deployment procedures.
Support production deployments, incident resolution, and ongoing maintenance of data engineering solutions.
Requirements
What we need
8+ years of overall Data Engineering experience.
Strong hands-on experience with Databricks and Apache Spark.
Proficiency in Python and Scala for data processing and application development.
Hands-on experience with Hadoop and big data technologies.
Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
Strong understanding of ETL/ELT processes, data transformations, and distributed data processing.
Experience in performance tuning, debugging, troubleshooting, and production support.
Strong SQL skills and understanding of data management concepts.
Excellent analytical, problem-solving, and collaboration skills.
Benefits
Why Join Tiger Analytics:
Drive High-Impact Business Transformation: Lead strategic engagements that go beyond traditional analytics, delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes.
Build and Lead at Global Scale: Collaborate with exceptional AI, data, engineering, and consulting talent across geographies to deliver transformative solutions and grow strategic client partnerships.
Benefits: Medical, Dental, Vision, Retirement Accounts, Long and Short Term Disability, Life Insurance, HSA/FSA Accounts (USA) and Discretionary time-off.
Continuous Learning & AI Upskilling: Stay ahead of the rapidly evolving AI landscape through continuous learning, hands-on exposure to emerging technologies, and opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms. Grow alongside a team that invests in developing future-ready skills and encourages innovation.
About Tiger Analytics
Tiger Analytics is a consulting firm that provides data analytics consulting services to businesses. The company specializes in data science, machine learning, and artificial intelligence. Tiger Analytics helps businesses to leverage data to make better decisions, improve operations, and drive growth. The company has worked with clients in a variety of industries, including healthcare, retail, finance, and technology.
